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PG Madhavan's Blog Posts Tagged 'Science' (8)

IoT Data Science & “DML” – match made in heaven?

DML stands for “Dynamical Machine Learning” (more in the book, “SYSTEMS Analytics for IoT Data Science”, 2017). This match is not surprising once you realize that DML & IoT are both based on the venerable Systems Theory. Let us dig deeper . . .

Consider IoT for industrial applications. A machine is instrumented with sensors, data are collected in real-time (or at intervals), communicated to the cloud where IoT Data Science…

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Added by PG Madhavan on September 11, 2017 at 12:30pm — No Comments

History as a guide to IoT growth trajectory

Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .

“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?

 I have often used this diagram to crisply define IoT.…

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Added by PG Madhavan on April 2, 2017 at 1:00pm — 1 Comment

NEXT Machine Learning Paradigm: “DYNAMICAL"​ ML

Dynamical ML is machine learning that can adapt to variations over time; it requires “real-time recursive” learning algorithms and time-varying data models such as the ones described in the blog,…

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Added by PG Madhavan on March 18, 2017 at 2:30pm — 1 Comment

IoT as a Metaphor

What exactly is “IoT”? Internet of Things, yes; but what does that mean?

Internet of Things is a structural definition; it says there are “Things” such as sensors and devices (on machines or people) connected together in a Network. So what? What does a Network of Sensors & Devices allow us to DO? What is the functional description of IoT?

Being able to connect things together is “table stakes” at the intelligence augmentation game. What…

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Added by PG Madhavan on October 16, 2016 at 9:30am — No Comments

Generalized Dynamical Machine Learning

In this year of Rudolf Kalman’s demise, this article is dedicated to his memory.

 

We introduce a new Machine Learning (ML) solution for Dynamical, Non-linear, In-Stream Analytics. Clearly, such a solution will accommodate Static, Linear and Offline (or any combination thereof) Machine Learning tasks. The value of such a solution is significant because the same…

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Added by PG Madhavan on September 18, 2016 at 8:00am — No Comments

Introducing SYSTEMS Analytics

As a new sub-discipline of Data Science, I notice that SYSTEMS Analytics is starting to get some traction! There are a couple of Analytics graduate level programs with *Systems* in its title (Stevens Institute of Technology and University of North Carolina are the only ones I know). Web search brings up NO books on *Systems* Analytics. With the publication of my book with *Systems* in the title, that gap has been filled now! “…

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Added by PG Madhavan on August 5, 2016 at 9:00am — 4 Comments

What exactly is Data Science?

Reading some recent blogs, I sense a level of angst among Data Science practitioners about the nature of their field. What exactly IS Data Science - a question that seems to lurk just below the surface . . .

As a young field of study and work, it will naturally take time for a definition of Data Science to crystallize. In the meantime, see if this works for you . . .…

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Added by PG Madhavan on July 26, 2016 at 3:00pm — 2 Comments

Prediction – the other dismal science?

An insightful person once said, “Prediction is like driving your car forward by looking only at the rearview mirror!”. If the road is dead-straight, you are good . . . UNLESS there is a stalled vehicle ahead in the middle of the road.

We should consider short-term and long-term prediction separately. Long-term prediction is nearly a lost cause. In the 80’s and 90’s, chaos and complexity theorists showed us that things can spin out of control even when we have perfect…

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Added by PG Madhavan on January 26, 2016 at 2:08pm — No Comments

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